Update app.py

app.py

@@ -19,53 +19,56 @@ GOOGLE_API_KEY=os.environ['GOOGLE_API_KEY']
 
 st.title('Stock Market Insights')
 
-ticker_user = st.text_input("Enter Ticker","ADANIENT")
-
-url1 = f"https://www.google.com/finance/quote/{ticker_user}:NSE?hl=en"
-url2 = f"https://in.tradingview.com/symbols/NSE-{ticker_user}/"
-
-loader = WebBaseLoader([url1,url2])
-docs = loader.load()
-
-gemini_embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
-
-llm = ChatGoogleGenerativeAI(model="gemini-pro",google_api_key = GOOGLE_API_KEY)
-
-st.divider()
-# llm_prompt_template = """You are an expert Stock Market Trader for stock market insights based on fundamental, analytical, profit based and company financials.
-# Based on the context below
-# {context}, Summarize the stock based on Historical data based on fundamental, price, news, sentiment , any red flags and suggest rating of the Stock in a 1 to 10 Scale"""
-
-llm_prompt_template = """You are an expert Stock Market Trader specializing in stock market insights derived from fundamental analysis, analytical trends, profit-based evaluations, and detailed company financials. Using your expertise, please analyze the stock based on the provided context below.
-
-Context:
-{context}
-
-Task:
-Summarize the stock based on its historical and current data.
-Evaluate the stock on the following parameters:
-1. Company Fundamentals: Assess the stock's intrinsic value, growth potential, and financial health.
-2. Current & Future Price Trends: Analyze historical price movements and current price trends.
-3. News and Sentiment: Review recent news articles, press releases, and social media sentiment.
-4. Red Flags: Identify any potential risks or warning signs.
-5. Provide a rating for the stock on a scale of 1 to 10.
-6. Advise if the stock is a good buy for the next 2 weeks.
-7. Suggest at what price we need to buy and hold or sell
-"""
-
-st.sidebar.subheader('Prompt')
-user_prompt = st.sidebar.text_area("Enter Prompt",llm_prompt_template)
-
-llm_prompt = PromptTemplate.from_template(user_prompt)
-
-llm_chain = LLMChain(llm=llm,prompt=llm_prompt)
-stuff_chain = StuffDocumentsChain(llm_chain=llm_chain,document_variable_name="context")
-
-
-res = stuff_chain.invoke(docs)
-
-
-st.write(res["output_text"])
+ticker_user = st.text_input("Enter Ticker")
+
+
+submit = st.button('Search')
+if submit:
+    url1 = f"https://www.google.com/finance/quote/{ticker_user}:NSE?hl=en"
+    url2 = f"https://in.tradingview.com/symbols/NSE-{ticker_user}/"
+    
+    loader = WebBaseLoader([url1,url2])
+    docs = loader.load()
+    
+    gemini_embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
+    
+    llm = ChatGoogleGenerativeAI(model="gemini-pro",google_api_key = GOOGLE_API_KEY)
+    
+    st.divider()
+    # llm_prompt_template = """You are an expert Stock Market Trader for stock market insights based on fundamental, analytical, profit based and company financials.
+    # Based on the context below
+    # {context}, Summarize the stock based on Historical data based on fundamental, price, news, sentiment , any red flags and suggest rating of the Stock in a 1 to 10 Scale"""
+    
+    llm_prompt_template = """You are an expert Stock Market Trader specializing in stock market insights derived from fundamental analysis, analytical trends, profit-based evaluations, and detailed company financials. Using your expertise, please analyze the stock based on the provided context below.
+    
+    Context:
+    {context}
+    
+    Task:
+    Summarize the stock based on its historical and current data.
+    Evaluate the stock on the following parameters:
+    1. Company Fundamentals: Assess the stock's intrinsic value, growth potential, and financial health.
+    2. Current & Future Price Trends: Analyze historical price movements and current price trends.
+    3. News and Sentiment: Review recent news articles, press releases, and social media sentiment.
+    4. Red Flags: Identify any potential risks or warning signs.
+    5. Provide a rating for the stock on a scale of 1 to 10.
+    6. Advise if the stock is a good buy for the next 2 weeks.
+    7. Suggest at what price we need to buy and hold or sell
+    """
+    
+    st.sidebar.subheader('Prompt')
+    user_prompt = st.sidebar.text_area("Enter Prompt",llm_prompt_template)
+    
+    llm_prompt = PromptTemplate.from_template(user_prompt)
+    
+    llm_chain = LLMChain(llm=llm,prompt=llm_prompt)
+    stuff_chain = StuffDocumentsChain(llm_chain=llm_chain,document_variable_name="context")
+    
+    
+    res = stuff_chain.invoke(docs)
+    
+    
+    st.write(res["output_text"])
 
 # If there is no environment variable set for the API key, you can pass the API
 # key to the parameter `google_api_key` of the `GoogleGenerativeAIEmbeddings`